This repository contains examples of using BrainPy to implement various models about neurons, synapse, networks, etc. We welcome your implementation, which can be post through our github page.
If you run some codes failed, please tell us through github issue https://github.com/brainpy/examples/issues .
If you found these examples are useful for your research, please kindly cite us.
If you want to add more examples, please fork our github https://github.com/brainpy/examples .
Example categories:
- Neuron Models
- Attractor Networks
- Decision Making Model
- E/I Balanced Network
- Brain-inspired Computing
- Reservoir Computing
- Gap Junction Network
- Oscillation and Synchronization
- Large-Scale Modeling
- Recurrent Neural Network
- Working Memory Model
- Dynamics Analysis
- Classical Dynamical Systems
- Unclassified Models
- (Izhikevich, 2003): Izhikevich Model
- (Brette, Romain. 2004): LIF phase locking
- (Gerstner, 2005): Adaptive Exponential Integrate-and-Fire model
- (Niebur, et. al, 2009): Generalized integrate-and-fire model
- (Jansen & Rit, 1995): Jansen-Rit Model
- (Teka, et. al, 2018): Fractional-order Izhikevich neuron model
- (Mondal, et. al, 2019): Fractional-order FitzHugh-Rinzel bursting neuron model
- CANN 1D Oscillatory Tracking
- (Si Wu, 2008): Continuous-attractor Neural Network 1D
- (Si Wu, 2008): Continuous-attractor Neural Network 2D
- Discrete Hopfield Network
- Discrete Hopfield Network Demo for Image Reconstruction
- (Vreeswijk & Sompolinsky, 1996): E/I balanced network
- (Brette, et, al., 2007): COBA
- (Brette, et, al., 2007): CUBA
- (Brette, et, al., 2007): COBA-HH
- (Tian, et al., 2020): E/I Net for fast response
- Classify MNIST dataset by a fully connected LIF layer
- Convolutional SNN to Classify Fashion-MNIST
- (2022, NeurIPS): Online Training Through Time for Spiking Neural Networks
- (2019, Zenke, F.): SNN Surrogate Gradient Learning
- (2019, Zenke, F.): SNN Surrogate Gradient Learning to Classify Fashion-MNIST
- (2021, Raminmh): Liquid time-constant Networks
- Predicting Mackey-Glass timeseries
- (Sussillo & Abbott, 2009): FORCE Learning
- (Gauthier, et. al, 2021): Next generation reservoir computing
- (Fazli and Richard, 2022): Electrically Coupled Bursting Pituitary Cells
- (Sherman & Rinzel, 1992): Gap junction leads to anti-synchronization
- (Wang & Buzsáki, 1996): Gamma Oscillation
- (Brunel & Hakim, 1999): Fast Global Oscillation
- (Diesmann, et, al., 1999): Synfire Chains
- (Li, et. al, 2017): Unified Thalamus Oscillation Model
- (Susin & Destexhe, 2021): Asynchronous Network
- (Susin & Destexhe, 2021): CHING Network for Generating Gamma Oscillation
- (Susin & Destexhe, 2021): ING Network for Generating Gamma Oscillation
- (Susin & Destexhe, 2021): PING Network for Generating Gamma Oscillation
- (Joglekar, et. al, 2018): Inter-areal Balanced Amplification Figure 1
- (Joglekar, et. al, 2018): Inter-areal Balanced Amplification Figure 2
- (Joglekar, et. al, 2018): Inter-areal Balanced Amplification Figure 5
- (Joglekar, et. al, 2018): Inter-areal Balanced Amplification Taichi customized operators
- Simulating 1-million-neuron networks with 1GB GPU memory
- (Sussillo & Abbott, 2009): FORCE Learning
- Integrator RNN Model
- Train RNN to Solve Parametric Working Memory
- (Song, et al., 2016): Training excitatory-inhibitory recurrent network
- (Masse, et al., 2019): RNN with STP for Working Memory
- (Yang, 2020): Dynamical system analysis for RNN
- (Bellec, et. al, 2020): eprop for Evidence Accumulation Task
- (Bouchacourt & Buschman, 2019): Flexible Working Memory Model
- (Mi, et. al., 2017): STP for Working Memory Capacity
- (Masse, et al., 2019): RNN with STP for Working Memory
- [1D] Simple systems
- [2D] NaK model analysis
- [2D] Wilson-Cowan model
- [2D] Decision Making Model with SlowPointFinder
- [2D] Decision Making Model with Low-dimensional Analyzer
- [3D] Hindmarsh Rose Model
- Continuous-attractor Neural Network
- Gap junction-coupled FitzHugh-Nagumo Model
- (Yang, 2020): Dynamical system analysis for RNN
- Hénon map
- Logistic map
- Lorenz system
- Mackey-Glass equation
- Multiscroll chaotic attractor (多卷波混沌吸引子)
- Rabinovich-Fabrikant equations
- Fractional-order Chaos Gallery